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Resource distribution can vary greatly in space and time. Consequently, animals should adjust their searching tactics to such spatio-temporal patterns in accordance with their innate capabilities, or alternatively, they should use a genetically fixed searching tactic that has been evolved in response to the specific pattern of the food they experience. Using a simulation model and a genetic algorithm, we show how optimal searching tactics change as a function of food spatial pattern. Searching tactics for hidden prey can be approximated using the following three components: (1) Extensive search mode (ESM), the type of movement before encountering a food item; (2) Intensive search mode (ISM), the type of movement after encountering a food item; and (3) ISM duration. Both ESM and ISM are characterized by movement tortuosity. We show that searching behavior adaptively changes as a function of food pattern. When food is distributed in a regular pattern, ISM is more directional than ESM, but under a clumped food pattern, ISM is much more tortuous than ESM. It may suggest that animals with larger spectra of searching tactics should experience greater variance or seasonal changes in their food pattern than animals with narrow spectra of searching tactics. Increased forager attack radius diminishes the differences between ESM and ISM, and thus the use of these three components to model searching in animals with higher attack radii is not appropriate. Increased handling time, which is a surrogate of reducing habitat profitability results in longer patch residency time as expected by optimal foraging theory. To conclude, we suggest that using such a combined approach of simulation models and genetic algorithms may improve our understanding of how extrinsic and intrinsic factors interact to influence searching behavior.